tf.contrib.learn.TensorFlowRNNRegressor.get_tensor(name) Returns tensor by name. Args: name: string, name of the tensor. Returns: Tensor.

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D Tensor. The product of the dimensions of the batch_shape is the number of independent distributions of this kind the instance represents. Args: name: name to give to the op Returns: batch_shape: Tensor.

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.zeros_like(tensor, dtype=None, name=None, optimize=True) Creates a tensor with all elements set to zero. Given a single tensor (tensor), this operation returns a tensor of the same type and shape as tensor with all elements set to zero. Optionally, you can use dtype to specify a new type for the returned tensor. For example: # 'tensor' is [[1, 2, 3], [4, 5, 6]] tf.zeros_like(tensor) ==> [[0, 0, 0], [0, 0, 0]] Args: tensor: A Tensor. dtype: A type for the returned Tensor. Must be float3

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.is_continuous

class tf.RandomShuffleQueue A queue implementation that dequeues elements in a random order. See tf.QueueBase for a description of the methods on this class.

tf.contrib.distributions.Mixture.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.graph_editor.reroute_b2a_ts(ts0, ts1, can_modify=None, cannot_modify=None) For each tensor's pair, replace the end of t0 by the end of t1. B0 B1 B0 B1 | | => | A0 A1 A0 A1 The end of the tensors in ts0 are left dangling. Args: ts0: an object convertible to a list of tf.Tensor. ts1: an object convertible to a list of tf.Tensor. can_modify: iterable of operations which can be modified. Any operation outside within_ops will be left untouched by this function. cannot_modify: iter

tf.python_io.tf_record_iterator(path, options=None) An iterator that read the records from a TFRecords file. Args: path: The path to the TFRecords file. options: (optional) A TFRecordOptions object. Yields: Strings. Raises: IOError: If path cannot be opened for reading.

tf.contrib.graph_editor.ControlOutputs.__init__(graph) Create a dictionary of control-output dependencies. Args: graph: a tf.Graph. Returns: A dictionary where a key is a tf.Operation instance and the corresponding value is a list of all the ops which have the key as one of their control-input dependencies. Raises: TypeError: graph is not a tf.Graph.